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Maximal Margin Classifiers
MP3•Episode home
Manage episode 192791981 series 74115
Content provided by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Maximal margin classifiers are a way of thinking about supervised learning entirely in terms of the decision boundary between two classes, and defining that boundary in a way that maximizes the distance from any given point to the boundary. It's a neat way to think about statistical learning and a prerequisite for understanding support vector machines, which we'll cover next week--stay tuned!
…
continue reading
293 episodes
MP3•Episode home
Manage episode 192791981 series 74115
Content provided by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Jaffe and Katie Malone, Ben Jaffe, and Katie Malone or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Maximal margin classifiers are a way of thinking about supervised learning entirely in terms of the decision boundary between two classes, and defining that boundary in a way that maximizes the distance from any given point to the boundary. It's a neat way to think about statistical learning and a prerequisite for understanding support vector machines, which we'll cover next week--stay tuned!
…
continue reading
293 episodes
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